Wednesday, May 01, 2013

Stuff To Read on Gender, With Some Echidne Analysis

Or stuff I could have written about had I gotten up earlier!

First, these stories are a way to show the gnat bites: The way views and ideas about women and men and the associated experiences accumulate in tiny gnat bites, so small that any crazy feminazi blogger who writes about them is told that she is making mountains out of mole-hills and should focus on more important stuff.

What that criticism ignores is the number of those gnat bites. Most of us would look like Swiss cheese after a few decades of living if each bite left a visible hole.

Researchers increasingly track variations in health outcomes across counties in the United States, but current ranking methods do not reflect changes in health outcomes over time. We examined trends in male and female mortality rates from 1992–96 to 2002–06 in 3,140 US counties. We found that female mortality rates increased in 42.8 percent of counties, while male mortality rates increased in only 3.4 percent. Several factors, including higher education levels, not being in the South or West, and low smoking rates, were associated with lower mortality rates. Medical care variables, such as proportions of primary care providers, were not associated with lower rates. These findings suggest that improving health outcomes across the United States will require increased public and private investment in the social and environmental determinants of health—beyond an exclusive focus on access to care or individual health behavior.

This is the crucial part of the study conclusions:

Mortality rates are falling in most US counties, but we found a large number of counties with no reductions in female mortality rates during the study period. We identified a number of factors most strongly associated with mortality change, including education levels, the region the county was located in, and smoking rates. Our results underscore the complicated policy reality that there is no single silver bullet for population health improvement. Investments in all determinants of health—including health care, public health, health behaviors, and residents’ social and physical environments—will be required.

Bolds are mine.

The difficulty of addressing this study and its importance hinges on the lack of certain pieces of data which really are needed. One of them the authors could have supplied but I can't find it, and that's the simple numbers. How many women live in those counties? When we are told that roughly half of all US counties show increasing female death rates, does it mean that the same percentage of US women find their rates rising?

That's not the correct interpretation, because then the overall female mortality rates would look different. My guess is that the counties we are talking about are low-population counties. But I still want to know the overall numbers affected.

The second bit of data we really need are internal migration rates. One reason for the findings could be that the women who leave those areas are the ones with the highest life expectancy rates and that the women who stay behind are the ones with more health problems. If these counties are mostly rural ones, women would have a higher exit rate than men, given the male-dominated aspects of agriculture. Or perhaps not. But this data is very important for understanding what is happening, and I guess it doesn't exist.

The above paragraph may sound academic. But it's not. It is very important. If the reason for the differences in the mortality rates is that healthier women have moved elsewhere, then the interpretation of the rates is very different than if the story is that something is affecting the mortality rates of all women in those areas.

I had a few other problems with the aggregate character of the data (it's county-level, not individual) and the fact that many of the included variables most likely correlate with each other in the data set, so it can be tricky to argue that education matters more than, say, income, given that the two tend to move together. Likewise, the study found race not significant in the regression analyses, even though we know that the average life expectancy rates differ quite a bit by race. The reason for that insignificance could be that the variables measuring geography (American south) and income capture any race differences.

Third, here's more about the discussion of Wikipedia and what happens to women authors (read both links and in the order shown here).

I find it interesting and wonder to what extent the anarchic nature of Wikipedia editing contributes to the scarcity of female editors. If I had to spend hours at those internal cafes defending my editing against MRA guys, say, you'd have to pay me. Hrmh. Just reminding that there is no free lunch, even for goddesses.

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